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QUANTITATIVE RESILIENCE ASSESSMENT OF CHEMICAL PROCESS SYSTEMS USING FUNCTIONAL RESONANCE ANALYSIS METHOD AND DYNAMIC BAYESIAN NETWORK

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dc.contributor.author Zinetullina, Altyngul
dc.contributor.author Yang, Ming
dc.contributor.author Khakzad, Nima
dc.contributor.author Golman, Boris
dc.contributor.author Li, Xinhong
dc.date.accessioned 2021-07-14T08:26:41Z
dc.date.available 2021-07-14T08:26:41Z
dc.date.issued 2021
dc.identifier.citation Zinetullina, A., Yang, M., Khakzad, N., Golman, B., & Li, X. (2021). Quantitative resilience assessment of chemical process systems using functional resonance analysis method and Dynamic Bayesian network. Reliability Engineering and System Safety, 205, [107232]. https://doi.org/10.1016/j.ress.2020.107232 en_US
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/5571
dc.description.abstract The emergent hazards of chemical process systems cannot be wholly identified and are highly uncertain due to the complicated technical-human-organizational interactions. Under uncertain and unpredictable circumstances, resilience becomes an essential property of a chemical process system that helps it better adapt to disruptions and restore from surprising damages. The resilience assessment needs to be enhanced to identify the accident's root causes on the level of technical-human-organizational interactions, and development of the specific resilience attributes to withstand or recover from the disruptions. The outcomes of resilience assessment are valuable to identify potential design or operational improvements to ensure complex process system functionality and safety... en_US
dc.language.iso en en_US
dc.publisher Reliability Engineering and System Safety en_US
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/ *
dc.subject resilience assessment en_US
dc.subject chemical process systems en_US
dc.subject dynamic Bayesian network en_US
dc.subject Open access en_US
dc.title QUANTITATIVE RESILIENCE ASSESSMENT OF CHEMICAL PROCESS SYSTEMS USING FUNCTIONAL RESONANCE ANALYSIS METHOD AND DYNAMIC BAYESIAN NETWORK en_US
dc.type Article en_US
workflow.import.source science


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